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Stiffness is a mechanical property of vital importance to any material system and is typically considered a static quantity. Recent work, however, has shown that novel materials with programmable stiffness can enhance the performance and simplify the design of engineered systems, such as morphing wings, robotic grippers, and wearable exoskeletons. For many of these applications, the ability to program stiffness with electrical activation is advantageous because of the natural compatibility with electrical sensing, control, and power networks ubiquitous in autonomous machines and robots. The numerous applications for materials with electrically driven stiffness modulation has driven a rapid increase in the number of publications in this field. Here, a comprehensive review of the available materials that realize electroprogrammable stiffness is provided, showing that all current approaches can be categorized as using electrostatics or electrically activated phase changes, and summarizing the advantages, limitations, and applications of these materials. Finally, a perspective identifies state‐of‐the‐art trends and an outlook of future opportunities for the development and use of materials with electroprogrammable stiffness.

The most common sensing modalities found in a robot perception system are vision and touch, which together can provide global and highly localized data for manipulation. However, these sensing modalities often fail to adequately capture the behavior of target objects during the critical moments as they transition out of static, controlled contact with an end-effector to dynamic and uncontrolled motion. In this work, we present a novel multimodal visuotactile sensor that provides simultaneous visuotactile and proximity depth data. The sensor integrates an RGB camera and air pressure sensor to sense touch with an infrared time-of-flight (ToF) camera to sense proximity by leveraging a selectively transmissive soft membrane to enable the dual sensing modalities. We present the mechanical design, fabrication techniques, algorithm implementations, and evaluation of the sensor's tactile and proximity modalities. The sensor is demonstrated in three open-loop robotic tasks: approaching and contacting an object, catching, and throwing. The fusion of tactile and proximity data could be used to capture key information about a target object's transition behavior for sensor-based control in dynamic manipulation.